In risk assessment of spatially distributed infrastructure, the probability of demand exceeding capacity is evaluated across the system. We describe and compare two levee system reliability analysis frameworks for seismic and high-water demands. The first approach considers spatial correlations and distributions of demand and capacity between “segments” (i.e., elemental levee lengths) through Monte Carlo simulation. We apply a capacity correlation model derived from seismic case histories in Japan. The seismic demand correlation model is based on global ground motion data, whereas the high-water correlation is taken as unity. The second approach examines the distribution and correlation of capacities and demands between physics-based “reaches” (i.e., length of levee having uniform statistical distributions of capacity and demand). Statistics and spatial correlation of the limit state function are computed using a first-order reliability method procedure. The probability of failure of the reach is then computed using level-crossing statistics. For implementation of level-crossing statistics, we replace Markov-type correlation functions for levee capacity with a Gaussian function. We illustrate both methods for a levee system subjected to realistic demand and capacity distributions and show that characteristic lengths (defined as lengths of levee that can be considered as statistically independent) are comparable for high-water and seismic demands. This outcome is specific to the considered failure mechanisms and is driven by use of similar capacity correlation models, whereas differences in demand correlation models have limited impact.
